Embedding Gaussian primitives into a ray tracing structure enables unified radio propagation simulation and view synthesis from visual-only reconstructions.
Sionna RT: Technical report
8 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 8representative citing papers
FARM is a foundation model combining masked autoencoders and diffusion decoders to estimate high-resolution aerial radio maps from a new multi-band low-altitude dataset, claiming superior accuracy and generalization over prior methods.
The paper provides an open-source configuration-driven simulator for sub-THz radio-stripe architectures that includes models for polymer microwave fiber, couplers, and configurable RF impairments.
An LLM-powered agentic framework autonomously designs competitive and sometimes superior explainable algorithms for wireless PHY and MAC layer tasks.
Telecom World Models introduce a three-layer architecture for learned, action-conditioned, uncertainty-aware modeling of 6G network dynamics, combining digital twins and foundation models, with a network slicing proof-of-concept showing improved KPI prediction over baselines.
An ellipsoid-guided selective refinement algorithm improves radio-map fidelity in urban wireless digital twins by prioritizing refinement of a small subset of buildings using only low-fidelity models.
PointNeRT is a neural surrogate for ray tracing that ingests point clouds and sequentially predicts multipath propagation and attenuation under physics constraints.
Linear regression on ray-tracing data predicts 7 GHz outdoor channel coefficients with MAE 7.5155e-5 and RMSE 9.2861e-5, beating SVR and decision-tree regression.
citing papers explorer
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Differentiable Ray Tracing with Gaussians for Unified Radio Propagation Simulation and View Synthesis
Embedding Gaussian primitives into a ray tracing structure enables unified radio propagation simulation and view synthesis from visual-only reconstructions.
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FARM: Foundational Aerial Radio Map for Intelligent Low-Altitude Networking
FARM is a foundation model combining masked autoencoders and diffusion decoders to estimate high-resolution aerial radio maps from a new multi-band low-altitude dataset, claiming superior accuracy and generalization over prior methods.
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An Open-Source Hardware-Aware Sub-THz Radio-Stripe Simulator
The paper provides an open-source configuration-driven simulator for sub-THz radio-stripe architectures that includes models for polymer microwave fiber, couplers, and configurable RF impairments.
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The AI Telco Engineer: Toward Autonomous Discovery of Wireless Communications Algorithms
An LLM-powered agentic framework autonomously designs competitive and sometimes superior explainable algorithms for wireless PHY and MAC layer tasks.
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Telecom World Models: Unifying Digital Twins, Foundation Models, and Predictive Planning for 6G
Telecom World Models introduce a three-layer architecture for learned, action-conditioned, uncertainty-aware modeling of 6G network dynamics, combining digital twins and foundation models, with a network slicing proof-of-concept showing improved KPI prediction over baselines.
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Fidelity Where it Matters: Site-Specific Nonuniform Refinement for Wireless Digital Twins
An ellipsoid-guided selective refinement algorithm improves radio-map fidelity in urban wireless digital twins by prioritizing refinement of a small subset of buildings using only low-fidelity models.
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PointNeRT: A Physics Aware Neural Ray Tracing Surrogate for Propagation Channel Modeling
PointNeRT is a neural surrogate for ray tracing that ingests point clouds and sequentially predicts multipath propagation and attenuation under physics constraints.
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Data driven approach for Outdoor Channel Prediction in 5G and Beyond
Linear regression on ray-tracing data predicts 7 GHz outdoor channel coefficients with MAE 7.5155e-5 and RMSE 9.2861e-5, beating SVR and decision-tree regression.